These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 24808458)

  • 1. Robustness analysis of global exponential stability of recurrent neural networks in the presence of time delays and random disturbances.
    Shen Y; Wang J
    IEEE Trans Neural Netw Learn Syst; 2012 Jan; 23(1):87-96. PubMed ID: 24808458
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Further results on robustness analysis of global exponential stability of recurrent neural networks with time delays and random disturbances.
    Luo W; Zhong K; Zhu S; Shen Y
    Neural Netw; 2014 May; 53():127-33. PubMed ID: 24613807
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Robustness analysis for connection weight matrices of global exponential stability of stochastic recurrent neural networks.
    Zhu S; Shen Y
    Neural Netw; 2013 Feb; 38():17-22. PubMed ID: 23201555
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Noise further expresses exponential decay for globally exponentially stable time-varying delayed neural networks.
    Zhu S; Yang Q; Shen Y
    Neural Netw; 2016 May; 77():7-13. PubMed ID: 26907861
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Global exponential stability of generalized recurrent neural networks with discrete and distributed delays.
    Liu Y; Wang Z; Liu X
    Neural Netw; 2006 Jun; 19(5):667-75. PubMed ID: 16046098
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Global exponential stability of recurrent neural networks with time-varying delays in the presence of strong external stimuli.
    Zeng Z; Wang J
    Neural Netw; 2006 Dec; 19(10):1528-37. PubMed ID: 17045459
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Stability analysis of discrete-time recurrent neural networks.
    Barabanov NE; Prokhorov DV
    IEEE Trans Neural Netw; 2002; 13(2):292-303. PubMed ID: 18244432
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Delay-dependent robust exponential stability for uncertain recurrent neural networks with time-varying delays.
    Zhang B; Xu S; Li Y
    Int J Neural Syst; 2007 Jun; 17(3):207-18. PubMed ID: 17640101
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved delay-dependent robust stability criteria for recurrent neural networks with time-varying delays.
    Liu PL
    ISA Trans; 2013 Jan; 52(1):30-5. PubMed ID: 22959741
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Global exponential stability of impulsive high-order BAM neural networks with time-varying delays.
    Ho DW; Liang J; Lam J
    Neural Netw; 2006 Dec; 19(10):1581-90. PubMed ID: 16580174
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Novel stability analysis for recurrent neural networks with multiple delays via line integral-type L-K functional.
    Liu Z; Zhang H; Zhang Q
    IEEE Trans Neural Netw; 2010 Nov; 21(11):1710-8. PubMed ID: 21047705
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Global exponential periodicity and stability of recurrent neural networks with multi-proportional delays.
    Zhou L; Zhang Y
    ISA Trans; 2016 Jan; 60():89-95. PubMed ID: 26639054
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Global exponential periodicity and global exponential stability of a class of recurrent neural networks with various activation functions and time-varying delays.
    Chen B; Wang J
    Neural Netw; 2007 Dec; 20(10):1067-80. PubMed ID: 17881187
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Impulsive control for existence, uniqueness, and global stability of periodic solutions of recurrent neural networks with discrete and continuously distributed delays.
    Li X; Song S
    IEEE Trans Neural Netw Learn Syst; 2013 Jun; 24(6):868-77. PubMed ID: 24808469
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Global exponential dissipativity and stabilization of memristor-based recurrent neural networks with time-varying delays.
    Guo Z; Wang J; Yan Z
    Neural Netw; 2013 Dec; 48():158-72. PubMed ID: 24055958
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A new approach to exponential stability analysis of neural networks with time-varying delays.
    Xu S; Lam J
    Neural Netw; 2006 Jan; 19(1):76-83. PubMed ID: 16153804
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Stability analysis of neural networks with interval time-varying delays.
    Hou YY; Liao TL; Lien CH; Yan JJ
    Chaos; 2007 Sep; 17(3):033120. PubMed ID: 17903002
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Exponential state estimation for Markovian jumping neural networks with time-varying discrete and distributed delays.
    Zhang D; Yu L
    Neural Netw; 2012 Nov; 35():103-11. PubMed ID: 22982094
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays.
    Cao J; Wang J
    Neural Netw; 2004 Apr; 17(3):379-90. PubMed ID: 15037355
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Global exponential periodicity and stability of discrete-time complex-valued recurrent neural networks with time-delays.
    Hu J; Wang J
    Neural Netw; 2015 Jun; 66():119-30. PubMed ID: 25839167
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.